Abstract. Biogeochemical models of the ocean carbon cycle are frequently validated by, or tuned to, satellite chlorophyll data. However, ocean carbon cycle models are required to accurately model the movement of carbon, not chlorophyll, and due to the high variability of the carbon to chlorophyll ratio in phytoplankton, chlorophyll is not a robust proxy for carbon. Using inherent optical property (IOP) inversion algorithms it is now possible to also derive the amount of light backscattered by the upper ocean (bb) which is related to the amount of particulate organic carbon (POC) present. Using empirical relationships between POC and bb, a 1-D marine biogeochemical model is used to simulate bb at 490 nm thereby allowing the model to be compared with both remotely-sensed chlorophyll or bb data. Here I investigate the possibility of using bb in conjunction with chlorophyll data to help constrain the parameters in a simple 1-D NPZD model. The parameters of the biogeochemical model are tuned with a genetic algorithm, so that the model is fitted to either chlorophyll data or to both chlorophyll and bb data at three sites in the Atlantic with very different characteristics. Several inherent optical property (IOP) algorithms are available for estimating bb, three of which are used here. The effect of the different bb datasets on the behaviour of the tuned model is examined to ascertain whether the uncertainty in bb is significant. The results show that the addition of bb data does not consistently alter the same model parameters at each site and in fact can lead to some parameters becoming less well constrained, implying there is still much work to be done on the mechanisms relating chlorophyll to POC and bb within the model. However, this study does indicate that including bb data has the potential to significantly effect the modelled mixed layer detritus and that uncertainties in bb due to the different IOP algorithms are not particularly significant.